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Protect community from confusable homoglyphs #1470
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d4e9256
protect community from confusable homoglyphs
MartinDelille 6f100de
adding confusable_homoglyphs to requirements_base.txt
MartinDelille b4d4c05
fix flake8 test
MartinDelille 4883243
update confusable_homoglyphs in make env step
MartinDelille 9b496bc
move unconfusable_string to liberapay/utils/unconfusable.py
MartinDelille 64033bd
disable confusable_homoglyphs update in make env
MartinDelille 03b1fa3
add spacing line in requirements_base.txt
MartinDelille 2a96f25
one liner import
MartinDelille a73af92
document unconfusable_string
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Original file line number | Diff line number | Diff line change |
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@@ -0,0 +1,11 @@ | ||
from confusable_homoglyphs import confusables | ||
|
||
def unconfusable_string(name): | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. It would be nice to have a docstring explaining what this function does. There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Done here: a73af92 Tell me if there is a specific format for that. |
||
unconfusable_name = '' | ||
for c in name: | ||
confusable = confusables.is_confusable(c, preferred_aliases=['COMMON', 'LATIN']) | ||
if confusable: | ||
# if the character is confusable we replace it with the first prefered alias | ||
c = confusable[0]['homoglyphs'][0]['c'] | ||
unconfusable_name += c | ||
return unconfusable_name |
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This is a very inefficient implementation, the more communities there are the slower it becomes. Also you're repeating an identical function call (
cls._unconfusable(name)
) in every loop iteration.There was a problem hiding this comment.
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Fixed here: 9b496bc
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You only fixed the repeated call, not the wider issue: this implementation is still inefficient.
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Which part is the most inefficient:
unconfusable_string
function?There was a problem hiding this comment.
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The fetching of all the existing community names from the database and the subsequent loop. That's linear complexity, O(n), with
n
being the number of existing communities.There was a problem hiding this comment.
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We should probably do something like this instead: